As for the first two works, the authors of [1]} state “Palazzo et al. [24] and Tirupattur et al. [34] appear to employ related but somewhat different encoders. We do not comment on these here since we do not have access to this code” (“[24]” and “[34]” are reference numbers within [1]} for  and ).
Also, in reference to , Li et al. [1]} state that they “do not have access to these datasets”.
This is clearly incorrect. Indeed, one of the co-authors of [1]}, Hamad Ahmed, contacted the first author of  on December 19, 2018 and asked for the code. 's first author sent him the code and data promptly and made everything available on Githubhttps://github.com/ptirupat/ThoughtViz. After that, there was no additional communication.
We believe Li et al. [1]} had enough time to run the provided code and analyze the results, instead of speculating on the results obtained in . Claiming that they were not given access to the code and the data, is simply incorrect.
The claim of insufficient detail to reproduce the code and the unavailability of the code described in  are, again, not true. Indeed, the architecture of the EEG encoder and the data are the same as in [6]},
while the code for the conditional GAN (whose architecture is a standard DC-GAN , as clearly stated in  and for which multiple implementations are available) is taken from , which is publicly availablehttps://github.com/reedscot/icml2016, and as such, couldn't be shared by us. The same discussion holds for  that used state of the art deep models.
This was also communicated to Jeffrey Mark Siskind on December, 19th 2018.
Finally, we did not release the code when the preprint was made available , since it was under review at PAMI (and recently accepted [7]}) and it might have been subject to changes during the peer-reviewing process. However, we believe that enough implementation details were available in the text to reproduce our work, since the dataset is the same of [6]}, and therefore readily available.
